In the mid-1980's, the long-standing historical decline in tuberculosis cases in the United States reversed itself and case rates began to rise. With the tuberculosis epidemic came the recognition that this disease was becoming increasingly concentrated in defined segments of the overall population. Though total case rates are falling again, groups in the US at significantly higher risk for tuberculosis than the general population exist. It is unknown whether the current recommendations for the control of tuberculosis in the US general population are as effective for these groups. To address this issue, a desktop Computer based mathematical model has been developed to simultaneously project tuberculosis cases and deaths over a l 0 year period using the best available epidemiological data. By adapting this model for US groups at increased risk for tuberculosis, this project will evaluate tuberculosis control strategies for four high risk groups. The groups are persons infected with human immunodeficiency virus, health care workers, immigrants, and the homeless. For each group, a database of inputs based on the epidemiology of tuberculosis within that group will be created. These databases will draw on the published literature and available government information such as that provided by the Centers for Disease Control and Prevention revised report of verified case of tuberculosis. The following tuberculosis control strategies will be evaluated singly and in combinations: increased coverage and improved efficacy of preventive therapy, increased coverage and improved efficacy of treatment, increased effectiveness of contact tracing, and the introduction of bacille Calmette-Guerin vaccination. The robustness of the model results will be assessed in sensitivity analyses by simultaneously varying all inputs using Latin hypercube sampling. The combination of mathematical modeling and epidemiology provides the most complete evaluation of TB control measures among these high risk groups to date, and forms a basis for improving approaches to control this epidemic among these populations.